Nonparametric particle filtering approaches for identification and inference in nonlinear state-space dynamic systems

Jean-Pierre Gauchi, Jean-Pierre Vila

Open source

DOI: 10.1007/s11222-012-9327-7
Published: 2012-03-30
Container: Statistics and Computing
Publisher: Springer Science and Business Media LLC
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1007/s11222-012-9327-7,
  title = {Nonparametric particle filtering approaches for identification and inference in nonlinear state-space dynamic systems},
  author = {Jean-Pierre Gauchi and Jean-Pierre Vila},
  year = {2012},
  journal = {Statistics and Computing},
  doi = {10.1007/s11222-012-9327-7},
  url = {https://doi.org/10.1007/s11222-012-9327-7}
}

RIS

TY  - JOUR
TI  - Nonparametric particle filtering approaches for identification and inference in nonlinear state-space dynamic systems
AU  - Jean-Pierre Gauchi
AU  - Jean-Pierre Vila
PY  - 2012
JO  - Statistics and Computing
DO  - 10.1007/s11222-012-9327-7
UR  - https://doi.org/10.1007/s11222-012-9327-7
ER  -

APA

Gauchi, J., & Vila, J. (2012). Nonparametric particle filtering approaches for identification and inference in nonlinear state-space dynamic systems. Statistics and Computing. https://doi.org/10.1007/s11222-012-9327-7

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crossref · retrieved 2026-11-10T10:44:10.620Z